Machine Learning-Based Approach for Hydrogen Economic Evaluation of Small Modular Reactors

In this study, we evaluate hydrogen production costs using small modular reactors (SMRs). Furthermore, we employ a machine learning-based approach to predict important parameters that affect the hydrogen production cost. Additionally, we use a hydrogen economic evaluation program to calculate the hydrogen production cost when using the two types of SMRs: system-integrated modular advanced reactor (SMART) developed by the Korea Atomic Energy Research Institute (KAERI) and NuScale power module (TM) (NPM) developed by the NuScale Power, LLC. Different storage and transportation means were selected to find the cheapest option. Using SMART, storing hydrogen in compressed gas and transporting it through pipes (CG-Pipe) is the best option, with an estimated cost of USD 2.77/kg. Other options when using SMART include storing in compressed gas and transporting with a vehicle (CG-Vehicle), with an estimated cost of USD 3.27/kg; storing by liquefaction and transporting with a vehicle (L-Vehicle), with an estimated cost of USD 3.31/kg; and storing in metal hydrides and transporting with a vehicle (MH-Vehicle), with an estimated cost of USD 6.97/kg. Using NPM, CG-Pipe is the cheapest option to generate hydrogen, with an estimated cost of USD 2.95/kg. Other options include CG-Vehicle (USD 3.35/kg), L-Vehicle (USD 3.42/kg), and MH-Vehicle (USD 7.04/kg). Hydrogen production using SMART is cheaper than using NPM. However, the observed difference between the hydrogen production costs using the two reactors was insignificant. We conclude that the optimal hydrogen production cost ranges from USD 3.27/kg (CG-Vehicle) to USD 3.42 (L-Vehicle). This conclusion is because the common hydrogen transportation means is with a vehicle. From a machine learning-based approach, we determine the important parameters that affect hydrogen production costs. The most important parameter is the heat consumption (MWth/unit) at hydrogen generation plants, and other parameters include electricity rating and heat for hydrogen generation plants.